An expert system based on linear discriminant analysis and adaptive neuro-fuzzy inference system to diagnosis heart valve diseases Abdulkadir Sengur Firat University, Department of Electronics and Computer Science, 23119, Elazig, Turkey Abstract In the last two decades, the use of artificial intelligence methods in biomedical analysis is increasing. This is mainly because of the effectiveness of classification and detection systems have improved in a great deal to help medical experts in diagnosing. In this paper, we investigate the use of linear discriminant analysis (LDA) and adaptive neuro-fuzzy inference system (ANFIS) to determine the normal and abnormal heart valves from the Doppler heart sounds. The proposed heart valve disorder detection system is composed of three stages. The first stage is the pre-processing stage. Filtering, normalization and white-denoising are the processes that were used in this stage. The feature extraction is the second stage. During feature extraction stage, Wavelet transforms and short-time Fourier transform were used. As next step, wavelet entropy was applied to these features. For reducing the complexity of the system, LDA was used for feature reduction. In the classification stage, ANFIS classifier is chosen. To evaluate the performance of proposed methodology, a com- parative study is realized by using a data set containing 215 samples. The validation of the proposed method is measured by using the sensitivity and specificity parameters. 95.9% sensitivity and 94% specificity rate was obtained. Ó 2007 Elsevier Ltd. All rights reserved. Keywords: Doppler heart sounds; Heart valves; Feature extraction; Wavelet decomposition; Feature reduction; Adaptive neuro-fuzzy inference system 1. Introduction The heart consists of four chambers, two atria and two ventricles. There is a valve through which blood passes before leaving each chamber of the heart. The valves prevent the backward flow of blood. These valves are actual flaps that are located on each end of the two ventricles (http:// www.healthsystem.virginia.edu/uvahealth/adult_cardiac/ disvalve.cfm). Heart valve disease is when one or more valves in the heart are not working fully and blood does not flow through the heart as it should. This can put an extra strain on the heart and cause symptoms such as breathless- ness and swollen ankles. Severe heart valve disease can cause the heart to pump less efficiently (http://hcd2.bupa.co.uk/ fact_sheets/html/heart_valve_disease.html). Heart valve disease may be suspected if the heart sounds heard through a stethoscope are abnormal. This is usually the first step in diagnosing a heart valve disease. A charac- teristic heart murmur (abnormal sounds in the heart due to turbulent blood flow) can often indicate valve regurgita- tion. To further define the type of valve disease and extent of the valve damage, physicians may use any of the follow- ing diagnostic procedures; electrocardiogram (ECG or EKG), chest X-ray, cardiac catheterization, transesopha- geal echo (TEE), radionuclide scans and magnetic reso- nance imaging (MRI) (Nanda, 1993). According to the researches most of human deaths in the world are due to heart diseases. For this reason, early detection of heart valve disorders is necessary in the medi- cal research areas (Akay, Akay, & Welkowitz, 1992). In the last decade, Doppler technique has gained much more interest since Satomura first demonstrated the application of the Doppler Effect to the measurement of blood velocity in 1959 (Keeton & Schlindwein, 1997). Doppler heart 0957-4174/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2007.06.012 E-mail address: ksengur@firat.edu.tr www.elsevier.com/locate/eswa Available online at www.sciencedirect.com Expert Systems with Applications 35 (2008) 214–222 Expert Systems with Applications